Parametric Design Practice: Algorithmic Form & Computational Geometry 参数化设计实践：算法形式与计算几何探索

参数化设计计算几何算法生成拓扑优化Grasshopper形态寻优数字建造

A research and design practice investigating rule-based morphogenesis, computational geometry, and algorithmic generative design. 聚焦规则生成、拓扑关系与参数驱动形式的计算设计实践，探索算法逻辑与空间几何在数字建造维度的融合表达。

Design Method 设计方法Algorithmic / 参数驱动

Core Toolchain 核心工具链Rhino / GH / Python

Geometry Logic 几何逻辑NURBS & Mesh

Status 阶段In Progress / 实践中

Reference / 参考信息

Chivalry Studio / Parametric Design Lab

Technical Stack / 技术框架

GrasshopperRhino 8PythonKangarooComputational GeometryTopology OptimizationParametric Modeling

01 / Generative Logic 规则生成

From static drafting to algorithmic logic. 从静态图面到算法驱动的动态生成系统。

The practice explores parametric modeling driven by mathematical functions, field forces, and cellular automata, translating conceptual constraints into dynamic topological structures. 实践围绕数学函数、力场引导与生长规则展开，将概念约束转化为自适应拓扑形体，建立输入参数与复杂几何的直接反馈回路。

02 / Computational Geometry 计算几何

Precise control of curvature, subdivision, and rationalization. 曲率连续性、网格细分与构建合理化控制。

Employing mesh relaxation, developable surface analysis, and panel rationalization to bridge computational abstraction with material fabrication constraints. 引入网格松弛、可展开曲面剖析与嵌板有理化算法，使复杂的流体曲面与离散单元在满足力学与制作规范的前提下达到形式与结构的平衡。

03 / Digital Iteration 数字化迭代

Performance-oriented multi-objective optimization. 面向性能与环境的多元目标优化迭代。

Integrating structural analysis and environmental simulation into parametric loops to automate performance feedback and structural material distribution. 将环境采光、受力分析等模拟引擎嵌入参数化工作流闭环中，通过多目标遗传算法实现基于性能反馈的设计演化。

Key Contributions / 核心贡献

Constructed algorithmic pipelines connecting mathematical rules to spatial geometries. / 构建连接数学规则与三维空间拓扑的生成管线。

Explored multi-parameter dynamic form-finding and topological relaxation. / 探索多参数动态形态寻优与拓扑松弛算法。

Rationalized freeform surfaces for panelization and digital fabrication. / 针对离散嵌板制造对复杂曲面进行有理化拆解与优化。

Integrated performance-based simulation feedback into design generation. / 将性能仿真与环境约束深度集成至参数化迭代闭环。